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Drought is one of the most devastating causes of yield losses in crops like maize, and the anticipated increases in severity and duration of drought spells due to climate change pose an imminent threat to agricultural productivity. To understand the drought response, phenotypic and molecular studies are typically performed at a given time point after drought onset, representing a steady-state adaptation response. Because growth is a dynamic process, we monitored the drought response with high temporal resolution and examined cellular and transcriptomic changes after rehydration at 4 and 6 days after leaf four appearance. These data showed that division zone activity is a determinant for full organ growth recovery upon rehydration. Moreover, a prolonged maintenance of cell division by the ectopic expression of PLASTOCHRON1 extends the ability to resume growth after rehydration. The transcriptome analysis indicated that GROWTH-REGULATING FACTORS (GRFs) affect leaf growth by impacting cell division duration, which was confirmed by a prolonged recovery potential of the GRF1-overexpression line after rehydration. Finally, we used a multiplex genome editing approach to evaluate the most promising differentially expressed genes from the transcriptome study and as such narrowed down the gene space from 40 to seven genes for future functional characterization., (© 2024 John Wiley & Sons Ltd.)

Objective: In this study, we investigate the potential of large language models (LLMs) to complement biomedical knowledge graphs in the training of semantic models for the biomedical and clinical domains., Materials and Methods: Drawing on the wealth of the Unified Medical Language System knowledge graph and harnessing cutting-edge LLMs, we propose a new state-of-the-art approach for obtaining high-fidelity representations of biomedical concepts and sentences, consisting of 3 steps: an improved contrastive learning phase, a novel self-distillation phase, and a weight averaging phase., Results: Through rigorous evaluations of diverse downstream tasks, we demonstrate consistent and substantial improvements over the previous state of the art for semantic textual similarity (STS), biomedical concept representation (BCR), and clinically named entity linking, across 15+ datasets. Besides our new state-of-the-art biomedical model for English, we also distill and release a multilingual model compatible with 50+ languages and finetuned on 7 European languages., Discussion: Many clinical pipelines can benefit from our latest models. Our new multilingual model enables a range of languages to benefit from our advancements in biomedical semantic representation learning, opening a new avenue for bioinformatics researchers around the world. As a result, we hope to see BioLORD-2023 becoming a precious tool for future biomedical applications., Conclusion: In this article, we introduced BioLORD-2023, a state-of-the-art model for STS and BCR designed for the clinical domain., (© The Author(s) 2024. Published by Oxford University Press on behalf of the American Medical Informatics Association.)

This paper introduces the Ghent Semi-spontaneous Speech Paradigm (GSSP), a new method for collecting unscripted speech data for affective-behavioral research in both experimental and real-world settings through the description of peer-rated pictures with a consistent affective load. The GSSP was designed to meet five criteria: (1) allow flexible speech recording durations, (2) provide a straightforward and non-interfering task, (3) allow for experimental control, (4) favor spontaneous speech for its prosodic richness, and (5) require minimal human interference to enable scalability. The validity of the GSSP was evaluated through an online task, in which this paradigm was implemented alongside a fixed-text read-aloud task. The results indicate that participants were able to describe images with an adequate duration, and acoustic analysis demonstrated a trend for most features in line with the targeted speech styles (i.e., unscripted spontaneous speech versus scripted read-aloud speech). A speech style classification model using acoustic features achieved a balanced accuracy of 83% on within-dataset validation, indicating separability between the GSSP and read-aloud speech task. Furthermore, when validating this model on an external dataset that contains interview and read-aloud speech, a balanced accuracy score of 70% is obtained, indicating an acoustic correspondence between the GSSP speech and spontaneous interviewee speech. The GSSP is of special interest for behavioral and speech researchers looking to capture spontaneous speech, both in longitudinal ambulatory behavioral studies and laboratory studies. To facilitate future research on speech styles, acoustics, and affective states, the task implementation code, the collected dataset, and analysis notebooks are available., (© 2023. The Author(s).)

Background: Thermography is a popular tool to assess plant water-use behavior, as plant temperature is influenced by transpiration rate, and is commonly used in field experiments to detect plant water deficit. Its application in indoor automated phenotyping platforms is still limited and mainly focuses on differences in plant temperature between genotypes or treatments, instead of estimating stomatal conductance or transpiration rate. In this study, the transferability of commonly used thermography analysis protocols from the field to greenhouse phenotyping platforms was evaluated. In addition, the added value of combining thermal infrared (TIR) with hyperspectral imaging to monitor drought effects on plant transpiration rate (E) was evaluated., Results: The sensitivity of commonly used TIR indices to detect drought-induced and genotypic differences in water status was investigated in eight maize inbred lines in the automated phenotyping platform PHENOVISION. Indices that normalized plant temperature for vapor pressure deficit and/or air temperature at the time of imaging were most sensitive to drought and could detect genotypic differences in the plants' water-use behavior. However, these indices were not strongly correlated to stomatal conductance and E. The canopy temperature depression index, the crop water stress index and the simplified stomatal conductance index were more suitable to monitor these traits, and were consequently used to develop empirical E prediction models by combining them with hyperspectral indices and/or environmental variables. Different modeling strategies were evaluated, including single index-based, machine learning and mechanistic models. Model comparison showed that combining multiple TIR indices in a random forest model can improve E prediction accuracy, and that the contribution of the hyperspectral data is limited when multiple indices are used. However, the empirical models trained on one genotype were not transferable to all eight inbred lines., Conclusion: Overall, this study demonstrates that existing TIR indices can be used to monitor drought stress and develop E prediction models in an indoor setup, as long as the indices normalize plant temperature for ambient air temperature or relative humidity., (© 2023. The Author(s).)

Plant organ growth results from the combined activity of cell division and cell expansion. The co-ordination of these two processes depends on the interplay between multiple hormones that determine the final organ size. Using the semidominant Hairy Sheath Frayed1 ( Hsf1 ) maize mutant that hypersignals the perception of cytokinin (CK), we show that CK can reduce leaf size and growth rate by decreasing cell division. Linked to CK hypersignaling, the Hsf1 mutant has an increased jasmonic acid (JA) content, a hormone that can inhibit cell division. The treatment of wild-type seedlings with exogenous JA reduces maize leaf size and growth rate, while JA-deficient maize mutants have increased leaf size and growth rate. Expression analysis revealed the increased transcript accumulation of several JA pathway genes in the Hsf1 leaf growth zone. A transient treatment of growing wild-type maize shoots with exogenous CK also induced the expression of JA biosynthetic genes, although this effect was blocked by the co-treatment with cycloheximide. Together, our results suggest that CK can promote JA accumulation, possibly through the increased expression of specific JA pathway genes.

Ensuring food security for an ever-growing global population while adapting to climate change is the main challenge for agriculture in the 21st century. Although new technologies are being applied to tackle this problem, we are approaching a plateau in crop improvement using conventional breeding. Recent advances in CRISPR/Cas9-mediated gene engineering have paved the way to accelerate plant breeding to meet this increasing demand. However, many traits are governed by multiple small-effect genes operating in complex interactive networks. Here, we present the gene discovery pipeline BREEDIT, which combines multiplex genome editing of whole gene families with crossing schemes to improve complex traits such as yield and drought tolerance. We induced gene knockouts in 48 growth-related genes into maize (Zea mays) using CRISPR/Cas9 and generated a collection of over 1,000 gene-edited plants. The edited populations displayed (on average) 5%-10% increases in leaf length and up to 20% increases in leaf width compared with the controls. For each gene family, edits in subsets of genes could be associated with enhanced traits, allowing us to reduce the gene space to be considered for trait improvement. BREEDIT could be rapidly applied to generate a diverse collection of mutants to identify promising gene modifications for later use in breeding programs., (© American Society of Plant Biologists 2022. All rights reserved. For permissions, please email: journals.permissions@oup.com.)

Modern agriculture is struggling to meet the increasing food, silage and raw material demands due to the rapid growth of population and climate change. In Arabidopsis, DA1 and DAR1 are proteases that negatively regulate cell proliferation and control organ size. DA1 and DAR1 are activated by ubiquitination catalyzed by the E3 ligase BIG BROTHER (BB). Here, we characterized the DA1, DAR1 and BB gene families in maize and analyzed whether perturbation of these genes regulates organ size similar to what was observed in Arabidopsis. We generated da1_dar1a_dar1b triple CRISPR maize mutants and bb1_bb2 double mutants. Detailed phenotypic analysis showed that the size of leaf, stem, cob, and seed was not consistently enlarged in these mutants. Also overexpression of a dominant-negative DA1 R333K allele, resembling the da1-1 allele of Arabidopsis which has larger leaves and seeds, did not alter the maize phenotype. The mild negative effects on plant height of the DA1 R333K _bb1_bb2 mutant indicate that the genes in the DA1 pathway may control organ size in maize, albeit less obvious than in Arabidopsis., (Copyright © 2022 Elsevier B.V. All rights reserved.)

Recently, the possibilities of detecting psychosocial stress from speech have been discussed. Yet, there are mixed effects and a current lack of clarity in relations and directions for parameters derived from stressed speech. The aim of the current study is - in a controlled psychosocial stress induction experiment - to apply network modeling to (1) look into the unique associations between specific speech parameters, comparing speech networks containing fundamental frequency (F0), jitter, mean voiced segment length, and Harmonics-to-Noise Ratio (HNR) pre- and post-stress induction, and (2) examine how changes pre- versus post-stress induction (i.e., change network) in each of the parameters are related to changes in self-reported negative affect. Results show that the network of speech parameters is similar after versus before the stress induction, with a central role of HNR, which shows that the complex interplay and unique associations between each of the used speech parameters is not impacted by psychosocial stress (aim 1). Moreover, we found a change network (consisting of pre-post stress difference values) with changes in jitter being positively related to changes in self-reported negative affect (aim 2). These findings illustrate - for the first time in a well-controlled but ecologically valid setting - the complex relations between different speech parameters in the context of psychosocial stress. Longitudinal and experimental studies are required to further investigate these relationships and to test whether the identified paths in the networks are indicative of causal relationships., (© 2021. The Author(s).)

The plant shoot apex houses the shoot apical meristem, a highly organized and active stem-cell tissue where molecular signaling in discrete cells determines when and where leaves are initiated. We optimized a spatial transcriptomics approach, in situ sequencing (ISS), to colocalize the transcripts of 90 genes simultaneously on the same section of tissue from the maize (Zea mays) shoot apex. The RNA ISS technology reported expression profiles that were highly comparable with those obtained by in situ hybridizations (ISHs) and allowed the discrimination between tissue domains. Furthermore, the application of spatial transcriptomics to the shoot apex, which inherently comprised phytomers that are in gradual developmental stages, provided a spatiotemporal sequence of transcriptional events. We illustrate the power of the technology through PLASTOCHRON1 (PLA1), which was specifically expressed at the boundary between indeterminate and determinate cells and partially overlapped with ROUGH SHEATH1 and OUTER CELL LAYER4 transcripts. Also, in the inflorescence, PLA1 transcripts localized in cells subtending the lateral primordia or bordering the newly established meristematic region, suggesting a more general role of PLA1 in signaling between indeterminate and determinate cells during the formation of lateral organs. Spatial transcriptomics builds on RNA ISH, which assays relatively few transcripts at a time and provides a powerful complement to single-cell transcriptomics that inherently removes cells from their native spatial context. Further improvements in resolution and sensitivity will greatly advance research in plant developmental biology., (© American Society of Plant Biologists 2021. All rights reserved. For permissions, please email: journals.permissions@oup.com.)